Optimal dosing of bulk material using mass-flow estimation and DEM simulation

2018 ◽  
Author(s):  
Gavneet Singh Chadha ◽  
Fabian Westbrink ◽  
Thomas Schutte ◽  
Andreas Schwung
Keyword(s):  
Mass Flow ◽  
Bulk Material ◽  
Dem Simulation ◽  
Flow Estimation ◽  
Optimal Dosing

scholarly journals Coal Flowability Control on Preventing Spillage on Conveyor Belt Through Modeling and Simulation for Improving its Performance

2021 ◽  
Vol 90 (1) ◽  
pp. 130-145
Author(s):  
Sabri Bahrun ◽  
Mohd Shahrizan Yusoff ◽  
Mohamad Sazali Said ◽  
Azmi Hassan
Keyword(s):  
Bulk Material ◽  
Extraction Process ◽  
Conveyor Belt ◽  
Underground Mines ◽  
Mining Site ◽  
Dem Simulation ◽  
Conveyor System ◽  
Average Production ◽  
And Performance ◽  
Belt Conveyors

Belt conveyors are generally used in mining plant areas, both surface and underground mines. The belt conveyor is mainly applied to transport the extracted bulk material from the mining site to delivery. The effectiveness of the extraction process depends on the reliability and durability of the conveyor belt system. In addition, conveyor performance is very important specially to control material flowability to prevent spills or other operational disturbances to optimize production throughput. However, the transfer chute and settling zone can cause some problems during the transfer process, such as material spills. This problem can reduce the function and performance of the conveyor belt. This paper discusses a design model to reduce the problem of spillage in the settling zone. The model was developed by compiling the previous defecting data from the durability of the conveyor system, then analyzed using Discrete Element Method (DEM) software and compared with bulk characteristics. The initial performance of certain conveyors is only capable of serving with an average production of 76% of the designed capacity while energy is consumed at full load. By applying the DEM simulation result, the blade gate can reduce the peak angle break in the depositional zone before exiting. After the analysis is completed using DEM, the conveyor increases the average production to 95% of the designed capacity. In conclusion, controlling the maximum belt load without spillage will reduce interruption on conveyor belt operation and maintenance costs therefore increase plant reliability and availability.

Genetic Algorithms Applied to Flow Estimation in a Two-Phase Flow With a Venturi Meter

2014 ◽  
Author(s):  
Manuel A. Borregales ◽  
Gilberto Nuñez ◽  
Jose Cappelletto ◽  
Miguel Asuaje
Keyword(s):  
Genetic Algorithms ◽  
Mass Flow ◽  
Computational Cost ◽  
Venturi Tube ◽  
Oil Reservoirs ◽  
Two Phase ◽  
Flow Estimation ◽  
Deep Waters ◽  
Rms Error ◽  
Almost All

Due to depletion of on-shore and superficial oil reservoirs, and impulsed by recent discoveries of oil reservoirs in off-shore ultra-deep waters, each of the processes and equipment in oil production required further improvements in order to save costs, space and to reduce weight off-shore. One way to accomplish this is without separators and with the use of online multiphase flowmeters. The most used flowmeter is the Venturi tube. Despite Venturi flowmeters having been used in almost all commercial multiphase flowmeters, there is not a single correlation that provides good results for predicting mass flow in each phase, for any flow pattern, mass quality, void fraction and/or fluids properties. Instead, many correlations have been published, based on experimental and/or field data, but the use of these correlations outside multiphase range conditions is doubtful. This study proposes a new methodology that uses genetic algorithms to find correlations that better fit a set of data, which allow determining the mass flow of a two-phase mix through a Venturi tube. For that purpose, binary trees and Prüfer encoding are used to accomplish this implementation. The correlations found in this new methodology provide lower values of RMS error, 1–3%, against correlations proposed by previous authors that show an RMS error range of 5–10%. This technique allows finding further correlations, regardless the number of parameters to be used, at a low computational cost, and it does not require previous information on the behaviour of the data.

Comparison of Sensor Configurations for Mass Flow Estimation of Turbocharged Diesel Engines

2012 ◽  
pp. 303-326 ◽  
Author(s):  
Tomáš Polóni ◽  
Boris Rohal’-Ilkiv ◽  
Daniel Alberer ◽  
Luigi del Re ◽  
Tor Arne Johansen
Keyword(s):  
Mass Flow ◽  
Diesel Engines ◽  
Flow Estimation

scholarly journals Application of Optimization Method for Calibration and Maintenance of Power-Based Belt Scale

Minerals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 412
Author(s):  
Kanishk Bhadani ◽  
Gauti Asbjörnsson ◽  
Erik Hulthén ◽  
Kristoffer Hofling ◽  
Magnus Evertsson
Keyword(s):  
Mass Flow ◽  
Cost Effective ◽  
Optimization Method ◽  
Conveyor Belt ◽  
Practical Implementation ◽  
Flow Estimation ◽  
Power Draw ◽  
Mass Balancing ◽  
Crushing Plant ◽  
Operational Data

Process optimization and improvement strategies applied in a crushing plant are coupled with the measurement of such improvements, and one of the indicators for improvements is the mass flow at different parts of the circuit. The estimation of the mass flow using conveyor belt power consumption allows for a cost-effective solution. The principle behind the estimation is that the power draw from a conveyor belt is dependent on the load on the conveyor, conveyor speed, geometrical design, and overall efficiency of the conveyor. Calibration of the power-based belt scale is carried out periodically to ensure the accuracy of the measurement. In practical implementation, certain conveyors are not directly accessible for calibration to the physical measurement as these conveyors have limited access or it is too costly to interrupt the ongoing production process. For addressing this limitation, a better strategy is needed to calibrate the efficiency of the power-based belt scale and maintain the reliability of such a system. This paper presents the application of an optimization method for a data collection system to calibrate and maintain accurate mass flow estimation. This includes calibration of variables such as the efficiency of the power-based belt scale. The optimization method uses an error minimization optimization formulation together with the mass balancing of the crushing plant to determine the efficiency of accessible and non-accessible conveyors. Furthermore, a correlation matrix is developed to monitor and detect deviations in the estimation for the mass flow. The methods are applied and discussed for operational data from a full-scale crushing plant.

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